Recently, as the number of cameras built into polydioptric cameras has increased, image rectification of these cameras has become complicated. However, because conventional methods cannot compensate for the calibration errors or are limited by the camera arrangement, they cannot be widely applied to various kinds of polydioptric cameras. In this work, we adopted the idea of disparity-error-minimization to overcome these limitations. We introduced the following several improvements in the optimization-based rectification. (1) We modified the objective function to include both the x and y disparity errors. (2) We added a regularization term to perform robustly for mismatched pairs. (3) We employed tri-level optimization to determine the camera pose corresponding to the rectified images. For two representative polydioptric cameras, this method reduced the average disparity error up to 66.57% compared to conventional methods. The results showed that our method exhibited significant generalization capabilities, achieving significant improvements over the existing methods.

近来，随着内置在多折射照相机中的照相机的数量增加，这些照相机的图像校正变得复杂。然而，由于常规方法不能补偿校准误差或受照相机布置的限制，因此它们不能广泛应用于各种多折射照相机。在这项工作中，我们采用了视差错误最小化的想法来克服这些限制。我们在基于优化的整流中引入了以下几项改进。（1）我们修改了目标函数，使其同时包含x和y视差误差。（2）我们添加了一个正则化项以对不匹配的对进行鲁棒地执行。（3）我们采用三级优化来确定与校正图像相对应的相机姿态。对于两个代表性的多折射相机，与传统方法相比，该方法将平均视差误差降低了66.57％。结果表明，我们的方法展现出显着的泛化能力，与现有方法相比有了显着改进。